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R session - Parenting-attention-WM.R
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R session - Parenting-attention-WM.R
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# The association between parenting, attention and working memory in early childhood
# Packages ----------------------------------------------------------------
install.packages("psych")
install.packages("PerformanceAnalytics")
install.packages("Hmisc")
library("Hmisc")
library(tidyverse)
library(naniar)
library(psych)
library(PerformanceAnalytics)
# Data files --------------------------------------------------------------
background <- read_csv("E:/Dissertation/Study 2/W_Background_Questionnaire.csv")
trackit <- read.csv("E:/Dissertation/Study 2/W Track-it Task data.csv")
wordspan <- read_csv("E:/Dissertation/Study 2/W Verbal WM.csv")
forwardtap <- read.csv("E:/Dissertation/Study 2/W Corsi Forward data.csv")
backwardtap <- read.csv("E:/Dissertation/Study 2/W Corsi Backward data.csv")
parenting <- read.csv("E:/Dissertation/Study 2/W Parenting.csv")
CBQ <- read.csv("E:/Dissertation/Study 2/W CBQ.csv")
spaceship <- read.csv("W SWMtask.csv")
study2 <- read_csv("study2.csv")
spaceship_mdntgt <- read.csv("E:/Dissertation/Study 2/Data for HLM/spaceship_mdntgt.csv")
Updated_SWMtask <- read_csv("Updated_SWMtask.csv")
# Background questionnaire ------------------------------------------------
background <- background %>%
filter(Subject <= 32066, Subject != 32026, Subject != 32027, Subject != 32032, Subject != 32039, Subject != 32040, Subject != 32048, Subject != 32059)
background$SEX <- ifelse(background$SEX == "M", 0, 1)
background <- background %>%
select(Subject, age = 'Age in years', sex = SEX, ratio)
dplyr::count(background, MEDU)
dplyr::count(background, FEDU)
dplyr::count(background, SEX)
dplyr::count(background, ranum)
dplyr::count(background, Ethnicity)
# Track-it ----------------------------------------------------------------
trackit <- as_tibble(trackit)
trackit <- select(trackit, -(Birthdate:Gender), -X)
trackit <- select(trackit, Subject = ID, everything())
trackit <- trackit %>%
filter(Subject <= 32066, Subject != 32026, Subject != 32027, Subject != 32032, Subject != 32039, Subject != 32040, Subject != 32048, Subject != 32059)
trackit <- filter(trackit, Memory.of.location != ".")
trackit$Memory.of.location <- as.numeric(trackit$Memory.of.location == "TRUE")
trackit <- trackit %>%
filter(Trial != 2 ) %>%
group_by(Subject) %>%
mutate(percentcorrect = sum(Memory.of.location)/10)
trackit <- trackit %>%
group_by(Subject) %>%
summarise(trackit_mean = mean (sum(percentcorrect)/10, na.rm = TRUE)) %>%
filter(trackit_mean != 0)
trackit %>%
ungroup(trackit) %>%
summarise(trackit_mean = mean(percentcorrect, na.rm = TRUE),
trackit_sd = sd(percentcorrect, na.rm = TRUE)) # Mean & sd for trackit
trackit_df <- filter(trackit, Trial == 2)# filter out test trials
# Forward Corsi-block tapping task ----------------------------------------
forwardtap <- forwardtap %>%
filter(Subject <= 32066,
Subject != 32026,
Subject != 32027,
Subject != 32032,
Subject != 32039,
Subject != 32040,
Subject != 32048,
Subject != 32059
)
forwardtap %>%
summarise(forwardtap_mean = mean(ftapsum, na.rm = TRUE),
forwardtap_sd = sd(ftapsum, na.rm = TRUE)
) #Screening data - outliers
forwardtap <- forwardtap %>%
filter(ftapsum != 0 & ftapsum != "NA")
# Backward Corsi-block tapping task ---------------------------------------
backwardtap <- backwardtap %>%
select(Subject = ID, bncorrect = ncorrect, bspan = span, btapsum = total.score)
backwardtap <- backwardtap %>%
filter(Subject <= 32066,
Subject != 32026,
Subject != 32027,
Subject != 32032,
Subject != 32039,
Subject != 32040,
Subject != 32048,
Subject != 32059
)
backwardtap <- backwardtap %>%
filter (btapsum != 0 & btapsum != "NA")
# Verbal working memory ---------------------------------------------------
wordspan <- wordspan %>%
select(Subject, wordspan = Score)
wordspan <- wordspan %>%
filter(Subject <= 32066,
Subject != 32026,
Subject != 32027,
Subject != 32032,
Subject != 32039,
Subject != 32040,
Subject != 32048,
Subject != 32059
)
wordspan <- wordspan %>%
filter(wordspan != 0 & wordspan != "NA")
wordspan <- mutate(wordspan, wordspan = wordspan + 1)
dplyr::count(wordspan, wordspan)
# Parenting behaviors and dimension questionnaire -------------------------
parenting <- as_tibble(parenting)
parenting <- parenting %>%
filter(Subject <= 32066,
Subject != 32026,
Subject != 32027,
Subject != 32032,
Subject != 32039,
Subject != 32040,
Subject != 32048,
Subject != 32059,
Subject !=32051
)
parenting <- select (parenting, -(Respondence:Sex))
warmth <- select(parenting, Subject, Q1, Q4, Q16, Q20, Q26, Q32)
punitive <- select(parenting, Subject, Q7, Q14, Q18, Q21, Q29)
autonomy <- select(parenting, Subject, Q2, Q8, Q19, Q25, Q30)
permissive <- select(parenting, Subject, Q5, Q9, Q15, Q24, Q27, Q31)
democratic <- select(parenting, Subject, Q10, Q12, Q17, Q23, Q33)
anxious <- select(parenting, Subject, Q3, Q6, Q11, Q13, Q22, Q28)
warmth <- warmth %>%
gather(`Q1`,`Q4`, `Q16`, `Q20`, `Q26`, `Q32`, key = "items", value = "warmthscore") %>%
group_by(Subject) %>%
summarise(warmthtotal = mean(warmthscore, na.rm = TRUE))
punitive <- punitive %>%
gather(`Q7`,`Q14`, `Q18`, `Q21`, `Q29`, key = "items", value = "punitivescore") %>%
group_by(Subject) %>%
summarise(punitivetotal = mean(punitivescore, na.rm = TRUE))
autonomy <- autonomy %>%
gather(`Q2`,`Q8`, `Q19`, `Q25`, `Q30`, key = "items", value = "autonomyscore") %>%
group_by(Subject) %>%
summarise(autonomytotal = mean(autonomyscore, na.rm = TRUE))
permissive <- permissive %>%
gather(`Q5`,`Q9`, `Q15`, `Q24`, `Q27`, `Q31`, key = "items", value = "permissivescore") %>%
group_by(Subject) %>%
summarise(permissivetotal = mean(permissivescore, na.rm = TRUE))
democratic <- democratic %>%
gather(`Q10`,`Q12`, `Q17`, `Q23`, `Q33`, key = "items", value = "demoscore") %>%
group_by(Subject) %>%
summarise(demototal = mean(demoscore, na.rm = TRUE))
anxious <- anxious %>%
gather(`Q3`,`Q6`, `Q11`, `Q13`, `Q22`,`Q28`, key = "items", value = "anxiousscore") %>%
group_by(Subject) %>%
summarise(anxioustotal = mean(anxiousscore, na.rm = TRUE))
parenting <- left_join(warmth, punitive, by = "Subject")
parenting <- left_join(parenting, autonomy, by = "Subject")
parenting <- left_join(parenting, permissive, by = "Subject")
parenting <- left_join(parenting, democratic, by = "Subject")
parenting <- left_join(parenting, anxious, by = "Subject")
parenting <- parenting %>%
select (Subject, warmth = warmthtotal, punitive = punitivetotal, autonomy = autonomytotal,permissive = permissivetotal, democratic = demototal, anxious = anxioustotal)
describe(parenting)
chart.Correlation(parenting[2:7],use = "pairwise.complete.obs", method = "spearman", exact = FALSE)
# Children's behavior questionnaire ---------------------------------------
CBQ <- as_tibble(CBQ)
CBQ <- CBQ %>%
filter(Subject <= 32066,
Subject != 32026,
Subject != 32027,
Subject != 32032,
Subject != 32039,
Subject != 32040,
Subject != 32048,
Subject != 32059,
Subject !=32017
)
CBQ <- CBQ %>%
mutate(Q38R = 8 - Q38, Q47R = 8 - Q47, Q171R = 8- Q171, Q195R = 8 - Q195, Q6R = 8 - Q6, Q95R = 8 - Q95, Q184R = 8 - Q184, Q71R = 8 - Q71, Q79R = 8 - Q79, Q90R = 8 - Q90, Q137R = 8 - Q137, Q169R = 8 - Q169, Q183R = 8 - Q183)
focusing <- select(CBQ, Subject, Q16, Q38R, Q47R, Q125, Q144, Q160,Q171R,Q186,Q195R)
shifting <- select(CBQ, Subject, Q6R, Q29, Q95R, Q180, Q184R)
impulsivity <- select(CBQ, Subject, Q13, Q26, Q46, Q59, Q71R,Q79R, Q90R,
Q104, Q114, Q137R, Q155, Q169R, Q183R)
focusing <- focusing %>%
gather(`Q16`, `Q38R`, `Q47R`, `Q125`, `Q144`, `Q160`, `Q171R`, `Q186`, `Q195R`, key = "items", value = "focusing") %>%
group_by(Subject) %>%
summarise( focusingtotal= mean(focusing, na.rm = TRUE))
shifting <- shifting %>%
gather(`Q6R`, `Q29`, `Q95R`, `Q180`, `Q184R`, key = "items", value = "shifting") %>%
group_by(Subject) %>%
summarise(shiftingtotal = mean(shifting, na.rm = TRUE))
impulsivity <- impulsivity %>%
gather(`Q13`, `Q26`, `Q46`, `Q59`, `Q71R`, `Q79R`, `Q90R`,
`Q104`, `Q114`, `Q137R`, `Q155`, `Q169R`, `Q183R`, key = "items", value = "impulsivity") %>%
group_by(Subject) %>%
summarise(impulsivitytotal = mean(impulsivity, na.rm = TRUE))
CBQ <- left_join(focusing, shifting, by = "Subject")
CBQ <- left_join(CBQ, impulsivity, by = "Subject")
CBQ <- CBQ %>%
select (Subject, cbqfocusing = focusingtotal, cbqshifting = shiftingtotal, cbqimpulsivity = impulsivitytotal)
# Merge data --------------------------------------------------------------
#export datafiles
write.csv(background, file = "background.csv", row.names = FALSE)
write.csv(parenting, file = "parenting.csv", row.names = FALSE)
write.csv(CBQ, file = "CBQ.csv", row.names = FALSE)
write.csv(trackit, file = "trackit.csv", row.names = FALSE)
write.csv(wordspan, file = "wordspan.csv", row.names = FALSE)
write.csv(forwardtap, file = "ftap.csv", row.names = FALSE)
write.csv(backwardtap, file = "btap.csv", row.names = FALSE)
write.csv(spaceship_median, file = "spaceship_median.csv", row.names = FALSE)
write.csv(spaceship_mdntgt, file = "spaceship_mdntgt.csv", row.names = FALSE)
write.csv(location, file = "location.csv", row.names = FALSE)
#merge data & export data
study2 <- left_join(background, parenting, by = "Subject")
study2 <- left_join(study2, CBQ, by = "Subject")
study2 <- left_join(study2, trackit, by = "Subject")
study2 <- left_join(study2, wordspan, by = "Subject")
study2 <- left_join(study2, forwardtap, by = "Subject")
study2 <- left_join(study2, backwardtap, by = "Subject")
study2 <- left_join(study2, spaceship_median, by = "Subject")
write.csv(study2, file = "study2.csv", row.names = FALSE)
# Spaceship task ----------------------------------------------------------
swm <- spaceship %>%
select(ExperimentName, Subject, Session, Delay, Trial,TargDeg, ABS_mm, errdir, errdis)
swm <- swm %>%
filter(Subject <= 32066,
Subject != 32026,
Subject != 32027,
Subject != 32032,
Subject != 32039,
Subject != 32040,
Subject != 32048,
Subject != 32059
)
swm5000 <- swm %>%
filter(Delay == 5000) %>%
filter(ABS_mm <= 203.7711)
swm5000 <- swm5000 %>%
mutate(errdir_new = case_when(TargDeg <0 ~ errdir*(-1),
TargDeg > 0 ~ errdir))
location <- swm5000 %>%
select(ExperimentName, Subject, Session, Trial, TargDeg, ABS_mm, errdir = errdir_new)
location <- location %>%
mutate(condition = stringr::str_sub(ExperimentName, 21, 21))
location <- location %>%
select(Subject, Session, Trial, TargDeg, ABS_mm, errdir, condition)
location$condition <- ifelse(location$condition == "L", 0, 1)
ggplot(data = swm5000) +
geom_histogram(mapping = aes(x = errdir), binwidth = 0.5)
swm_descriptive <- swm %>%
group_by(TargDeg) %>%
summarise(errdir_mean = mean(errdir, na.rm = TRUE),
errdir_sd = sd(errdir, na.rm = TRUE),
errdir_min = min(errdir, na.rm = TRUE),
errdir_max = max(errdir, na.rm = TRUE),
)
swm %>%
filter(Delay == 5000) %>%
summarise(ABS_mean = mean(ABS_mm, na.rm = TRUE),
ABS_sd = sd(ABS_mm, na.rm = TRUE))
swm5000 %>%
summarise(ABS_mean = mean(ABS_mm, na.rm = TRUE),
ABS_sd = sd(ABS_mm, na.rm = TRUE),
ABS_min = min(ABS_mm, na.rm = TRUE),
ABS_max = max(ABS_mm, na.rm = TRUE))
location_errabs <- location %>%
group_by(Subject) %>%
summarise(ABS_mean = mean(ABS_mm, na.rm = TRUE),
#ABS_sd = sd(ABS_mm, na.rm = TRUE),
#ABS_median = median(ABS_mm, na.rm = TRUE),
errdir_mean = mean(errdir, na.rm = TRUE),
#errdir_sd = sd(errdir, na.rm = TRUE),
#errdir_median = median(errdir, na.rm = TRUE)
)#within individual variablity
study2 <- left_join(study2, location_errabs, by = "Subject")
res2 <- rcorr(as.matrix(study2))
res2
res2$r
res2$P
study2_r <- res2$r
study2_P <- res2$P
write.csv(study2_r, file = "study2_r.csv")
write.csv(study2_P, file = "study2_P.csv")
spaceship_median <- location %>%
group_by(Subject, condition) %>%
summarise(ABS_mean = mean(ABS_mm, na.rm = TRUE),
ABS_median = median(ABS_mm, na.rm = TRUE),
errdir_mean = mean(errdir, na.rm = TRUE),
errdir_median = median(errdir, na.rm = TRUE),
errdis_mean = mean(errdis, na.rm = TRUE),
errdis_median = median(errdis, na.rm = TRUE)
)
spaceship_mdntgt <- location %>%
group_by(Subject, TargDeg, condition) %>%
summarise(ABS_mean = mean(ABS_mm, na.rm = TRUE),
ABS_median = median(ABS_mm, na.rm = TRUE),
errdir_mean = mean(errdir, na.rm = TRUE),
errdir_median = median(errdir, na.rm = TRUE),
errdis_mean = mean(errdis, na.rm = TRUE),
errdis_median = median(errdis, na.rm = TRUE)
)
### spaceship data descriptive statistics
location_age <- location %>%
mutate(Target = case_when(TargDeg <0 ~ TargDeg*(-1),
TargDeg > 0 ~ TargDeg)
) %>%
select(Subject, Target, ABS_mm, errdir) %>%
group_by(Subject, Target) %>%
summarise(errdir = mean(errdir, na.rm = TRUE),
ABS = mean(ABS_mm, na.rm = TRUE)
)
location_study2 <- left_join(location_age, study2, by = "Subject")
describe(location_study2, na.rm = TRUE, interp=FALSE,skew = TRUE, ranges = TRUE,trim=.1,type=3,check=TRUE,fast=NULL,quant=NULL,IQR=FALSE,omit=FALSE)
location_study2$Target <- as.factor(location_study2$Target)
location_study2_age <- location_study2 %>%
mutate(agegroup = case_when( age < 3.78 ~ 1,
age < 4.11 & age >= 3.78 ~ 2,
age < 4.44 & age >= 4.11 ~ 3,
age >= 4.44 ~ 4)
)
location_study2_age$agegroup <- as.factor(location_study2_age$agegroup)
ggplot(data = location_study2_age) +
geom_smooth(mapping = aes(x = democratic, y = errdir, color = Target))+
facet_wrap(~ agegroup, nrow = 2)
# ---plot for errdir & ABS by target location ------------------------------
spaceship_mdntgt <- location %>%
group_by(Subject, TargDeg) %>%
summarise(ABS_mean = mean(ABS_mm, na.rm = TRUE),
errdir_mean = mean(errdir, na.rm = TRUE)
)
spaceship_mdntgt <- spaceship_mdntgt %>%
mutate(Target = case_when(TargDeg <0 ~ TargDeg*(-1),
TargDeg > 0 ~ TargDeg)
)
spaceship_mdntgt$Target <- as.factor(spaceship_mdntgt$Target)
ggplot(data = spaceship_mdntgt, mapping = aes(x = Target, y = errdir_mean)) +
geom_boxplot() + # for errdir_mean
theme_bw() + theme(panel.border = element_blank(), panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))
ggplot(data = spaceship_mdntgt, mapping = aes(x = Target, y = ABS_mean)) +
geom_boxplot() + ## for ABS_mean
theme_bw() + theme(panel.border = element_blank(), panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))
df <- spaceship_tgt %>%
group_by(TargDeg) %>%
summarise(ABS = mean(ABS_mean, na.rm = TRUE), errdir = mean(errdir_mean, na.rm = TRUE), errdis = mean(errdis_mean, na.rm = TRUE))
barplot(errdir ~ TargDeg, data = df)
barplot(ABS ~ TargDeg, data = df)
spaceship_mdntgt_wide <- spaceship_mdntgt %>%
mutate(Target = case_when(TargDeg <0 ~ TargDeg*(-1),
TargDeg > 0 ~ TargDeg))
spaceship_mdntgt_wide %>%
pivot_wider(names_from = Target, values_from = ABS_median)
# -- ABS by TargDeg --------------------------------------------
df3 <- spaceship_mdntgt_wide %>%
pivot_wider(names_from = Target, values_from = ABS_mean)
df3 <- df3 %>%
select(Subject, `60`, `40`, `20`,`10`, `5`)
df3 <- df3 %>%
group_by(Subject) %>%
summarise(ABS_m_60 = mean(`60`, na.rm = TRUE),ABS_m_40 = mean(`40`, na.rm = TRUE),ABS_m_20 = mean(`20`, na.rm = TRUE),ABS_m_10 = mean(`10`, na.rm = TRUE),ABS_m_5 = mean(`5`, na.rm = TRUE))
ABS_mean <- df3
# -- errdir by TargDeg ----------------------------------------------------
df4 <- spaceship_mdntgt_wide %>%
pivot_wider(names_from = Target, values_from = errdir_mean)
df4 <- df4 %>%
select(Subject, `60`, `40`, `20`,`10`, `5`)
df4 <- df4 %>%
group_by(Subject) %>%
summarise(errdir_m_60 = mean(`60`, na.rm = TRUE),errdir_m_40 = mean(`40`, na.rm = TRUE),errdir_m_20 = mean(`20`, na.rm = TRUE),errdir_m_10 = mean(`10`, na.rm = TRUE),errdir_m_5 = mean(`5`, na.rm = TRUE))
errdir_mean <- df4
# --- correlation betwen variables ----------------------------------------
swmtarget <- left_join(ABS_mean, errdir_mean, by = "Subject")
write.csv(swmtarget, file = "swmtarget.csv", row.names = FALSE)
Study2 <- left_join(Study2, swmtarget, by = "Subject")
chart.Correlation(Study2[2:7],use = "pairwise.complete.obs", method = "spearman", exact = FALSE)
# Multiple Linear Regression Models ---------------------------------------
# linear regression
# wordspan
study2 <- read.csv("E:/Dissertation/Study 2/Data for HLM ERRDIR no transformation/study2.csv")
wordspan1 <- lm(wordspan~ age + ratio, data = study2)
summary(wordspan1)
wordspan2 <- lm(wordspan~ age + warmth + autonomy + democratic + cbqfocusing + cbqshifting + trackit_mean, data = study2)
summary(wordspan2)
# ftapsum
ftapsum1 <- lm(ftapsum ~ age + ratio, data = study2)
summary(ftapsum1)
ftapsum2 <- lm(ftapsum ~ age + warmth + autonomy + democratic + cbqfocusing + cbqshifting + trackit_mean, data = study2)
summary(ftapsum2)
# btapsum
btapsum1 <- lm(btapsum ~ age + ratio, data = study2)
summary(btapsum1)
btapsum2 <- lm(btapsum ~ age + warmth + autonomy + democratic + cbqfocusing + cbqshifting + trackit_mean, data = study2)
summary(btapsum2)
# Dummy code: TargDeg -----------------------------------------------------
location <- location %>%
mutate(target = case_when(TargDeg <0 ~ TargDeg*(-1),
TargDeg > 0 ~ TargDeg))
location$target60 <- ifelse(location$target == "60", 1, 0)
location$target40 <- ifelse(location$target == "40", 1, 0)
location$target10 <- ifelse(location$target == "10", 1, 0)
location$target5 <- ifelse(location$target == "5", 1, 0)